Malicious node traceback in opportunistic networks using merkle trees

Alajeely, Majeed, Ahmad, Asma'a and Doss, Robin 2015, Malicious node traceback in opportunistic networks using merkle trees, in DSDIS 2015: Proceedings of the IEEE International Conference on Data Science and Data Intensive Systems, IEEE, Piscataway, N.J., pp. 147-152, doi: 10.1109/DSDIS.2015.86.

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Title Malicious node traceback in opportunistic networks using merkle trees
Author(s) Alajeely, Majeed
Ahmad, Asma'a
Doss, RobinORCID iD for Doss, Robin orcid.org/0000-0001-6143-6850
Conference name IEEE International Conference on Data Science and Data Intensive Systems (2015 : Sydney, New South Wales)
Conference location Sydney, New South Wales
Conference dates 11-13 Dec. 2015
Title of proceedings DSDIS 2015: Proceedings of the IEEE International Conference on Data Science and Data Intensive Systems
Editor(s) Chen, J.
Yang, L.T.
Publication date 2015
Start page 147
End page 152
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) opportunistic networks
OppNets
security
packet dropping attacks
denial-of-service
malicious node detection
Summary Security is a major challenge in Opportunistic Networks because of its characteristics, such as open medium, dynamic topology, no centralized management and absent clear lines of defense. A packet dropping attack is one of the major security threats in OppNets since neither source nodes nor destination nodes have the knowledge of where or when the packet will be dropped. In this paper, we present a malicious nodes detection mechanism against a special type of packet dropping attack where the malicious node drops one or more packets and then injects new fake packets instead. Our novel detection and traceback mechanism is very powerful and has very high accuracy. Each node can detect and then traceback the malicious nodes based on a solid and powerful idea that is, Merkle tree hashing technique. In our defense techniques we have two stages. The first stage is to detect the attack, and the second stage is to find the malicious nodes. We have compared our approach with the acknowledgement based mechanisms and the networks coding based mechanism which are well known approaches in the literature. Simulation results show this robust mechanism achieves a very high accuracy and detection rate.
ISBN 9781509002146
Language eng
DOI 10.1109/DSDIS.2015.86
Field of Research 080303 Computer System Security
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30083232

Document type: Conference Paper
Collection: School of Information Technology
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